def multiply(m1, m2, n, routine=multiplication.strassen):
assert m1.nCols == n and m1.nRows % n == 0 and m2.nRows == n and m2.nCols % n == 0 or m2.nCols == n and m2.nRows % n == 0 and m1.nRows == n and m1.nCols % n == 0
if m1.nRows > m1.nCols:
c = list(
routine(matrix.Submatrix(m1, i * n, 0, n, n),
matrix.Submatrix(m2, 0, j * n, n, n))
for i in range(m1.nRows / n) for j in range(m2.nCols / n))
return matrix.Matrix(
list(concatenate(c, m1.nRows / n, m2.nCols / n, n, n)), m1.nRows,
m2.nCols)
else:
return sum((routine(matrix.Submatrix(m1, 0, i * n, n, n),
matrix.Submatrix(m2, i * n, 0, n, n))
for i in range(m1.nCols / n)), matrix.empty(n, n))
def diag(ins):
if isinstance(ins, matrix.Matrix):
min = ins.m if ins.m < ins.n else ins.n
temp = []
for x in xrange(1, min+1):
temp.append(str(ins.get(x,x)))
ret = matrix.Matrix(';'.join(temp))
elif isinstance(ins, list):
ret = zeros(len(ins))
for x in xrange(1, ret.m+1):
ret.set(x, x, ins[x-1])
else:
print >> sys.stderr, 'ERROR the parameter must be a matrix or list.'
ret = None
return ret
def multiply(m1, m2, n, routine=multiplication.strassen):
assert m1.nCols == n and m1.nRows % n == 0 and m2.nRows == n and m2.nCols % n == 0 or m2.nCols == n and m2.nRows % n == 0 and m1.nRows == n and m1.nCols % n == 0
if m1.nRows > m1.nCols:
c = list(
routine(matrix.Submatrix(m1, i * n, 0, n, n),
matrix.Submatrix(m2, 0, j * n, n, n))
for i in range(m1.nRows / n) for j in range(m2.nCols / n))
return matrix.Matrix(
list(concatenate(c, m1.nRows / n, m2.nCols / n, n, n)), m1.nRows,
m2.nCols)
else:
return sum((routine(matrix.Submatrix(m1, 0, i * n, n, n),
matrix.Submatrix(m2, i * n, 0, n, n))
for i in range(m1.nCols / n)), matrix.empty(n, n))
def random_array(n, m, p=0):
return [random.randint(p, m) for x in range(n)]
if __name__ == '__main__':
n = 8
k = 10
m1 = matrix.Matrix(random_array(n * n * k, 10), n * k, n)
m2 = matrix.Matrix(random_array(n * n * k, 10), n, n * k)
assert multiply(m1, m2, n) == m1 * m2
assert multiply(m2, m1, n) == m2 * m1
def custom(m, n, elem):
row = [str(elem)] * n
raw_matrix = ';'.join([','.join(row)] * m)
ret = matrix.Matrix(raw_matrix)
return ret
from __future__ import print_function
from matrix import multiplication, matrix
import benchmark.inputs
import benchmark.profiler
if __name__ == '__main__':
n = 8
m1 = matrix.Matrix(benchmark.inputs.random_array(pow(2, n * 2), 100, -100),
pow(2, n), pow(2, n))
m2 = matrix.Matrix(benchmark.inputs.random_array(pow(2, n * 2), 100, -100),
pow(2, n), pow(2, n))
p = benchmark.profiler.profile
#print(m1*m2)
r = [
p(multiplication.strassen, m1, m2),
p(multiplication.divide_and_conquer, m1, m2),
p(multiplication.simple, m1, m2)
]
#print(r)